843 citations · 1.1k across the 5 of their papers we have counts for
5 papers
When Can Transformers Count to n?
Gilad Yehudai, Haim Kaplan, Guy Dar +4
Large language models based on the transformer architecture can solve highly complex tasks, yet their fundamental limitations on simple algorithmic problems remain poorly understoo…
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Petko Georgiev, Ving Ian Lei +1132
In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over…
Gemini: A Family of Highly Capable Multimodal Models
Gemini Team, Rohan Anil, Sebastian Borgeaud +1340
This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consist…
Compositional Video Synthesis with Action Graphs
Amir Bar, Roei Herzig, Xiaolong Wang +4
Videos of actions are complex signals containing rich compositional structure in space and time. Current video generation methods lack the ability to condition the generation on mu…
Learning Infinite-Layer Networks: Without the Kernel Trick
Roi Livni, Daniel Carmon, Amir Globerson
Infinite--Layer Networks (ILN) have recently been proposed as an architecture that mimics neural networks while enjoying some of the advantages of kernel methods. ILN are networks…